Lingua: Inglese
Editore: Cambridge University Press, 2020
ISBN 10: 1108485065 ISBN 13: 9781108485067
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Lingua: Inglese
Editore: Cambridge University Press, 2020
ISBN 10: 1108485065 ISBN 13: 9781108485067
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hardcover. Condizione: Good. May contain some writing/highlighting. Cover shows wear from normal use. Supplemental materials such as CDs or access codes are not included unless otherwise noted.
Lingua: Inglese
Editore: Cambridge University Press, 2020
ISBN 10: 1108485065 ISBN 13: 9781108485067
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Lingua: Inglese
Editore: Cambridge University Press, 2020
ISBN 10: 1108485065 ISBN 13: 9781108485067
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Lingua: Inglese
Editore: Cambridge University Press, 2020
ISBN 10: 1108485065 ISBN 13: 9781108485067
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Lingua: Inglese
Editore: Cambridge University Press, GB, 2020
ISBN 10: 1108485065 ISBN 13: 9781108485067
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Aggiungi al carrelloHardback. Condizione: New. This book provides an introduction to the mathematical and algorithmic foundations of data science, including machine learning, high-dimensional geometry, and analysis of large networks. Topics include the counterintuitive nature of data in high dimensions, important linear algebraic techniques such as singular value decomposition, the theory of random walks and Markov chains, the fundamentals of and important algorithms for machine learning, algorithms and analysis for clustering, probabilistic models for large networks, representation learning including topic modelling and non-negative matrix factorization, wavelets and compressed sensing. Important probabilistic techniques are developed including the law of large numbers, tail inequalities, analysis of random projections, generalization guarantees in machine learning, and moment methods for analysis of phase transitions in large random graphs. Additionally, important structural and complexity measures are discussed such as matrix norms and VC-dimension. This book is suitable for both undergraduate and graduate courses in the design and analysis of algorithms for data.
Lingua: Inglese
Editore: Cambridge University Press, 2020
ISBN 10: 1108485065 ISBN 13: 9781108485067
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Lingua: Inglese
Editore: Cambridge University Press, 2020
ISBN 10: 1108485065 ISBN 13: 9781108485067
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Lingua: Inglese
Editore: Cambridge University Press 2020-01-23, 2020
ISBN 10: 1108485065 ISBN 13: 9781108485067
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Lingua: Inglese
Editore: Cambridge University Press, 2020
ISBN 10: 1108485065 ISBN 13: 9781108485067
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Lingua: Inglese
Editore: Cambridge University Press CUP, 2020
ISBN 10: 1108485065 ISBN 13: 9781108485067
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Lingua: Inglese
Editore: Cambridge University Press, 2020
ISBN 10: 1108485065 ISBN 13: 9781108485067
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Lingua: Inglese
Editore: Cambridge University Press, GB, 2020
ISBN 10: 1108485065 ISBN 13: 9781108485067
Da: Rarewaves.com UK, London, Regno Unito
EUR 69,85
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Aggiungi al carrelloHardback. Condizione: New. This book provides an introduction to the mathematical and algorithmic foundations of data science, including machine learning, high-dimensional geometry, and analysis of large networks. Topics include the counterintuitive nature of data in high dimensions, important linear algebraic techniques such as singular value decomposition, the theory of random walks and Markov chains, the fundamentals of and important algorithms for machine learning, algorithms and analysis for clustering, probabilistic models for large networks, representation learning including topic modelling and non-negative matrix factorization, wavelets and compressed sensing. Important probabilistic techniques are developed including the law of large numbers, tail inequalities, analysis of random projections, generalization guarantees in machine learning, and moment methods for analysis of phase transitions in large random graphs. Additionally, important structural and complexity measures are discussed such as matrix norms and VC-dimension. This book is suitable for both undergraduate and graduate courses in the design and analysis of algorithms for data.
Lingua: Inglese
Editore: Cambridge University Press, 2020
ISBN 10: 1108485065 ISBN 13: 9781108485067
Da: Biblios, Frankfurt am main, HESSE, Germania
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